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A short course of lectures
«Econometrics»





SpecificationProperties of the least squares estimatorThe log-linear specificationThe Durbins h test statisticTesting the regression equationThe t-distributionGLS when AR(1)The linear specificationThe F-distributionThe structural and reduced form equationOmission of a relevant variableDummy variablesPartial marginal effectsThe log-log specificationStatistical testsEstimation methodsBasic probability distributions in econometricsA model will intercept and slope dummy variableType I and type II errorsConsequencesThe rank condition of identificationStatistical inferenceThe adjusted coefficient of determination (Adjusted R2)Simultaneous equation modelsCharacteristics of probability distributionsGLS when AR(2)Measures of dispersionGraphical methodsChoosing the functional formRemedial measuresModel MeasuresSlope dummy variablesTest for structural differencesThe analysis of variance table (ANOVA)Heteroskedasticity-robust standard errorsIntercept dummy variablesIndirect Least Squares (ILS)The method of ordinary least squaresTesting a subset of coefficientsThe econometric modelConsequencesThe population regression modelThe probability function - the continuous caseConsequences of using OLSThe simple regression modelRandom variables and probability distributionsAutocorrelation and diagnosticsProperties of probabilitiesDetection of autocorrelationMeasures of central tendencyQualitative variables with several categoriesInclusion of an irrelevant variableThe multivariate probability distribution functionDetecting heteroskedasticityThe multiple regression modelPiecewise linear regressionMeasurement errorsTwo Stage Least Squares (2SLS)The LM-testMulticollinearity and diagnosticsThe linear-log specificationRemedial measuresThe joint hypothesis testIdentificationThe best linear predictorThe Durbin Watson testThe coefficient of determination (R2)The normal distributionDefinition and the nature of autocorrelationThe Chi-square distributionP-value in hypothesis testingBasics of probability and statisticsRemedial measuresThe cumulative probability function - the continuous caseThe assumptions of the simple regression modelConfidence intervalHypothesis testingSkewness and kurtosisThe cumulative probability function - the discrete caseHeteroskedasticity and diagnosticsThe probability function - the discrete caseMeasures of linear relationshipEstimation of population parametersThe economic modelThe order condition of identificationEstimation of partial regression coefficientsMeasuring the degree of multicollinearity
 
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